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FUME 2.0 – Flexible Universal processor for Modeling Emissions
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SYSNO ASEP 0585895 Druh ASEP J - Článek v odborném periodiku Zařazení RIV J - Článek v odborném periodiku Poddruh J Článek ve WOS Název FUME 2.0 – Flexible Universal processor for Modeling Emissions Tvůrce(i) Belda, M. (CZ)
Benešová, N. (CZ)
Resler, Jaroslav (UIVT-O) SAI, RID, ORCID
Huszár, P. (CZ)
Vlček, O. (CZ)
Krč, Pavel (UIVT-O) SAI, RID, ORCID
Karlický, J. (CZ)
Juruš, Pavel (UIVT-O) SAI, RID
Eben, Kryštof (UIVT-O) SAI, RID, ORCIDZdroj.dok. Geoscientific Model Development. - : Copernicus GmbH - ISSN 1991-959X
Roč. 17, č. 9 (2024), s. 3867-3878Poč.str. 12 s. Forma vydání Online - E Jazyk dok. eng - angličtina Země vyd. DE - Německo Klíč. slova Air quality modelling ; Emission modelling ; SMOKE ; emission inventories ; CTM Obor OECD Meteorology and atmospheric sciences CEP TO01000219 GA TA ČR - Technologická agentura ČR SS02030031 GA TA ČR - Technologická agentura ČR Způsob publikování Open access Institucionální podpora UIVT-O - RVO:67985807 UT WOS 001222533900001 EID SCOPUS 85193542888 DOI https://doi.org/10.5194/gmd-17-3867-2024 Anotace This paper introduces FUME 2.0, an open-source emission processor for air quality modeling, and documents the software structure, capabilities, and sample usage. FUME provides a customizable framework for emission preparation tailored to user needs. It is designed to work with heterogeneous emission inventory data, unify them into a common structure, and generate model-ready emissions for various chemical transport models (CTMs). Key features include flexibility in input data formats, support for spatial and temporal disaggregation, chemical speciation, and integration of external models like MEGAN. FUME employs a modular Python interface and PostgreSQL/PostGIS backend for efficient data handling. The workflow comprises data import, geographical transformation, chemical and temporal disaggregation, and output generation steps. Outputs for mesoscale CTMs CMAQ, CAMx, and WRF-Chem and the large-eddy-simulation model PALM are implemented along with a generic NetCDF format. Benchmark runs are discussed on a typical configuration with cascading domains, with import and preprocessing times scaling near-linearly with grid size. FUME facilitates air quality modeling from continental to regional and urban scales by enabling effective processing of diverse inventory datasets. Pracoviště Ústav informatiky Kontakt Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800 Rok sběru 2025 Elektronická adresa https://doi.org/10.5194/gmd-17-3867-2024
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